Evaluating the Spacing Effect Theory on the Instructional Effectiveness of Semester-Length versus Quarter-Length Introductory Computer Literacy Courses in Institutions of Higher Learning
Bibliographic record
Abstract
Evaluating the Spacing Effect Theory on the Instructional Effectiveness of Semester-Length versus Quarter-Length Introductory Computer Literacy Courses in Institutions of Higher Learning. Emelda S. Ntinglet-Davis 2013: Applied Dissertation, Nova Southeastern University, Abraham S. Fischler School of Education and Human Services. ERIC Descriptors: Community College, Spacing effect, Retention, Scheduling, Education, Instructional effectiveness, Intensive format, Quarter-length format, Semester format. This mixed research study evaluated the spacing effect theory on the academic performances of students enrolled in introductory level Computer Literacy courses by comparing course grades and mock IC3 certification exam scores in semester-length and quarter-length courses at Prince Georges Community College. The study was ingrained on the spacing effect theory which posits that mammals will tend to recall material learned over time (spaced presentation) than material concepts learned over shorter periods (massed presentation). A t test analysis revealed that students in the quarter-length formats had significantly higher grades than those in the semester format but presented no significant difference on their mock IC3 scores. A Pearson correlation conducted also revealed no significant relationship among students' course grades and their mock IC3 scores overall or by format (semester vs. intensive).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.027 | 0.078 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".